Squad AI

SquadAI is the Kubernetes-like control plane for Codex agents turning every event into the right Codex task, on the machines where the work already lives!

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Inspiration

Agents have become really good at getting things done but they kind of need the manual human input for every small thing.

I came across an analogy on social media that says LLM is the brain and skills/tools are hands. Then I thought what is missing to make it more autonomous?

I believe answer is - senses, which I think corresponds to event driven waking up of agents. A way for agents to react when something happens, rather than waiting for a person to open a chat and give them work.

Another big reason for me starting SquadAI is I think people use codex or any other agent just like another app, write skills around it or basic automations. But its much more powerful than that if we consider agent as a component in our system designs. For that programmatic access is needed and the ability to scale the agents automatically. I have 6 yrs of experience working with distributed systems at scale, thought it would be really cool to have the same concepts applied to AI agents as well :).

What it does

SquadAI is the infrastructure layer for running Codex agents as part of your systems not just as individual chat windows.

It lets your agents wake up and react to changes (events) in the world. Example of changes/events :

  1. Ops tickets coming in, your script/monitor detects it and sends over,
  2. New work item created in jira,
  3. Flight price changes,
  4. Or anything around which a script/monitor can be written which can then send events to SquadAI

Not only that, SquadAI also handles routing it to the right agent, queueing it, creating or resuming agent instances, managing persistent threads, shared library of skills, coordinating work across machines and giving you one place to see and control it all.

Also, added the support to talk to multiple agents through telegram group, the agents could be on any machine and still have the relevant context of the group chat!

Basically, SquadAI is a full control plane for your Codex agents. It turns individual agents into a system that can run, coordinate, and scale across any number of machines.

SquadAI architecture

What differentiates SquadAI from other solutions in same space?

Recently lot of solutions have come out to run agents on cloud. But as a developer/user I would like my agents running on the machine where my setup, files or apps are already there. Squad AI makes it flexible for the users to install the runners (wrapper around codex app server) on any machine they like and connect to the same control plane. As an user you would get a unified view of all the machines.

Few important design decisions: Lot of other solutions which support multiple machine, they require 1 agent to ssh into another machine and run commands there. This is not the case with SquadAI, no agent ssh-ing around, the agents live on their machine unaware of the other machine, all the communication is done through control plane. This makes the path for agent to agent communications across machines easier to handle.

Agents are treated as instantiable objects (borrowed few concepts from Object Oriented Programming), which allows the control plane to easily instantiate a copy of same agent automatically. You don't need to worry about creating agents manually for same task.

How I built it

  1. I came across codex app server which is really powerful and the backbone of the project.
  2. Made a wrapper around the codex app server APIs so the control plane above it can use it easily.
  3. Control plane was built which handles the event listening, queuing of tasks, routing the task to right agent etc. GPT-5.6 sol was used for this as it was bit complex piece.
  4. Built a completely new dashboard for visualizing the agents in a 3D topology view, and mainly the aim for it was to get an unified view of all the agents even if they are running on multiple machines. Codex made it easier by giving me images first to select the design and the coding it up. Annotation mode is super useful in building UI.
  5. Initially I had made it just keeping event driven waking up in mind (the famous loop engineering), then I realized why not have support for multiple machines and that's when i decoupled the control plane and codex app server wrapper code. Again gpt 5.6 sol helped here!
  6. Added support for tailscale to connect multiple machines easily.
  7. Once the event driven control and support for multiple machines was in place, then it was relatively easier to build any feature on top of it like for example the telegram group for agents.
  8. Whole project was completely built using codex and 5.6 terra/sol combination. That's why i say - built by codex for codex :)

Challenges I ran into

I didn't want to make a new UI at first as its really tough for people to adapt to new UI and codex desktop app already has a good one. But the issue is the threads started by custom code were not being actively displayed on the app. It does get displayed eventually but i wanted more synchronous way. And codex desktop app doesn't natively support listening to events. Had to take a route of creating the whole UI and wrapper on app server apis. Also, i am not good at networking part, gpt 5.6 suggested the tailscale solution!

Accomplishments that I am proud of

I have used it to automate the initial level of debugging required for ops tickets and I dont even need to do anything manually for 12 hrs straight.
Looking at it work on its own for long makes me confident about the project and happy with its current state. Also, really proud of the fact I was able to make a mini distributed system all by myself with the help of codex.

What I learned

I realized the power of agent and LLM is not just in chat window but in treating them as intelligent components in any of your system design, to make the agents truly autonomous. While working on the project learned about solutions like tailscale for networking.

What's next for Squad AI

There is a lot of work that needs to be done but next immediate plan for Squad AI is to support graphs, IYKYK :). Few other interesting areas are to automatically scale agents across machines and agent to agent communication across machines. In future, I also want to onboard more agents so that project is not specific to codex only.

Pre-existing work disclosure

I had started working on the project before the build week. Before the build week I had the wrapper around codex app server API and control plane code with UI.

During the build week I added the support for tailscale to be able to easily connect multiple machines, added shared skill library making it easier to transfer skills from one machine to another and added the whole telegram group chat integration supporting multiple agent tagging, conversation context handling and reply to msg feature. Few other changes were around making improvements in UI and fixing windows specific bugs.

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